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Sensor Calibration Record Quality Audit and Adjacent Row Changes
x402
Sensor Calibration Record Quality Audit and Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).
Audits sensor calibration records for quality issues and detects adjacent row changes across reference_value and sensor_value fields for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sensor calibration — Record quality audit + Adjacent row changes: Record quality audit + Adjacent row changes for supplied sensor calibration records (reference_value, sensor_value). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two analytical reports: (1) a record quality audit identifying data completeness issues, null values, format problems, and anomalies in the calibration rows; and (2) an adjacent row changes report highlighting where consecutive rows show value changes in the selected field (reference_value or sensor_value). Both reports are computed locally against the supplied data with no external lookups.
Example use cases
Calibration log quality check before analysis
“I have a batch of 80 sensor calibration records from group-a and group-b stations with dates and both reference and sensor values. Can you run a quality audit on them and flag any adjacent row changes in the sensor_value field so I can clean the data before I start my analysis?”
Detecting step changes in reference readings
“I need to find sudden jumps or changes between consecutive rows in my calibration dataset — about 150 rows of reference_value and sensor_value readings across multiple station groups. Can you run the adjacent row changes report on the reference_value field for me?”
Pre-submission data integrity validation
“Before I submit my sensor calibration log to the review board, can you do a full record quality audit and adjacent row change check on my 120-row dataset? Each row has a row_id, station_group, date, reference_value, and sensor_value.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-20-011?utm_source=zero.xyzWhen to prefer
Use this endpoint when you have sensor calibration data with reference and sensor value pairs and need both a record-level quality audit and adjacent row change detection in a single call. It is ideal for preprocessing calibration logs before statistical analysis, detecting step changes in time series sensor data, or validating data integrity before reporting. Best when you have up to 200 rows and need two complementary diagnostic reports at low cost without any external data lookups or live predictions.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, reference_value, sensor_value) — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (-1e12 to 1e12) — rejection
- Empty rows array — minimum items constraint violated
- Invalid field enum value (must be reference_value or sensor_value) — schema error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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